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The Role of Management Techniques for High-Performance Pending Interest Table: A Survey

  • Raaid Alubady
  • Suhaidi Hassan
  • Adib Habbal
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1073)

Abstract

Most of the services used by Internet consumers such as social network platforms, video-on-demand, on-line gaming, web Media, and IP Television which are content-centric in nature; meaning they focus on named content objects instead of being focused on the host-location. In this context, many projects around named data propose redesigning and developing the communication of Internet-based on named data. NDN (Named Data Networking) is an ideal solution to achieve efficient data sharing and retrieval since NDN focuses on the contents themselves regardless of their sources. The focus of this survey is a unique characteristic presented by NDN; PIT (Pending Interest table). PIT is part of three fundamental data structures newly introduced in the NDN router to enable full functionality of NDN. NDN router depends on reverse paths in PIT to return back Data packets to consumers. Accordingly, the PIT may present stringent restrictions in terms of scalability, for-warding, and management. The challenging task is the design of a scalable and manageable PIT because it requires per-packet updating and controlling the impact of increasing Interest packets with the highest Interest lifetime of PIT. Therefore, this survey describes into greater detail the background and several important previous researches related to issues of PIT which is PIT management based on PIT placement, and replacement, PIT implementation as a data structure, and Adaptive Interest Life-time. Thus, would assist in defining the general framework of this survey.

Keywords

Named Data Networking Pending Interest Table Interest lifetime Data structure And replacement policy 

References

  1. 1.
    Cha, M., Kwak, H., Rodriguez, P., Ahn, Y.Y., Moon, S.: Analyzing the video popularity characteristics of large-scale user generated content systems. IEEE/ACM Trans. Netw. 17(5), 1357–1370 (2009)CrossRefGoogle Scholar
  2. 2.
    Fazea, Y.: Numerical simulation of helical structure mode-division multiplexing with nonconcentric ring vortices. Opt. Commun. 437, 303–311 (2019)CrossRefGoogle Scholar
  3. 3.
    Fazea, Y.: Mode division multiplexing and dense WDM-PON for Fiber-to-the-Home. Optik (Stuttg) 183, 994–998 (2019)CrossRefGoogle Scholar
  4. 4.
    Fazea, Y., Alobaedy, M.M., Ibraheem, Z.T.: Performance of a direct-detection spot mode division multiplexing in multimode fiber. J. Opt. Commun. 40, 161–166 (2019)CrossRefGoogle Scholar
  5. 5.
    Fazea, Y., Mezhuyev, V.: Selective mode excitation techniques for mode-division multiplexing: a critical review. Opt. Fiber Technol. 45, 280–288 (2018)CrossRefGoogle Scholar
  6. 6.
    Fazea, Y., Sajat, M.S., Ahmad, A., Alobaedy, M.M.: Channel optimization in mode division multiplexing using neural networks. In: 2018 IEEE 14th International Colloquium on Signal Processing & Its Applications (CSPA), pp. 173–175 (2018)Google Scholar
  7. 7.
    Ibraheem, Z.T., Rahman, M.M., Fazea, Y., Ahmed, K.K.: PAPR reduction in OFDM signal by incorporating Mu-Law companding approach into enhanced PTS scheme. J. Opt. Commun.Google Scholar
  8. 8.
    Passarella, A.: A survey on content-centric technologies for the current internet: CDN and P2P solutions. Comput. Commun. 35(1), 1–32 (2012)CrossRefGoogle Scholar
  9. 9.
    Ejaz, W., Azam, M.A., Saadat, S., Iqbal, F., Hanan, A.: Unmanned aerial vehicles enabled IoT platform for disaster management. Energies 12(14), 1–19 (2019)CrossRefGoogle Scholar
  10. 10.
    Mathieu, B., Truong, P., Peltier, J.-F., You, W., Simon, G.: Information-centric networking: current research activities and challenges. In: Hassnaa, M., Sherali, Z. (eds.) Media Networks - Architectures, Applications, and Standards, pp. 141–184 (2012)Google Scholar
  11. 11.
    Jacobson, V., Smetters, D., Briggs, N., Thornton, J., Plass, M., Braynard, R.: Networking named content. In: Proceedings of the 5th International Conference on Emerging Networking Experiments and Technologies, pp. 1–12 (2009)Google Scholar
  12. 12.
    Saxena, D., Raychoudhury, V., Neeraj, S., Becker, C., Cao, J.: Named data networking: a survey. Comput. Sci. Rev. 19, 15–55 (2016)MathSciNetCrossRefGoogle Scholar
  13. 13.
    Xylomenos, G., et al.: A survey of information-centric networking research. IEEE Commun. Surv. Tutor. 16(2), 1–25 (2014)CrossRefGoogle Scholar
  14. 14.
    Bari, M.F., Chowdhury, S.R., Ahmed, R., Boutaba, R., Mathieu, B.: A survey of naming and routing in information-centric networks. IEEE Commun. Mag. 50(12), 44–53 (2012)CrossRefGoogle Scholar
  15. 15.
    Amadeo, M., Molinaro, A., Ruggeri, G.: E-CHANET: routing, forwarding and transport in information-centric multihop wireless networks. Comput. Commun. 36(7), 792–803 (2013)CrossRefGoogle Scholar
  16. 16.
    Abu, A.J., Bensaou, B., Wang, J.M.: Interest packets retransmission in lossy CCN networks and its impact on network performance. In: Proceedings of the 1st International Conference on Information-Centric Networking - INC 2014, pp. 167–176 (2014)Google Scholar
  17. 17.
    Afanasyev, A., Moiseenko, I., Zhang, L.: ndnSIM: NDN Simulator for NS-3, University of California, Los Angeles. Technical report NDN-0005, California, Los Angeles, pp. 1–7 (2012)Google Scholar
  18. 18.
    Alubady, R., Hassan, S., Habbal, A.: A taxonomy of pending interest table implementation approaches in named data networking. J. Theoret. Appl. Inf. Technol. 91(2), 411–423 (2016)Google Scholar
  19. 19.
    Dai, H., Liu, B., Chen, Y., Wang, Y.: On pending interest table in named data networking. In: Proceedings of the Eighth ACM/IEEE Symposium on Architectures for Networking and Communications Systems - ANCS 2012, pp. 211–222 (2012)Google Scholar
  20. 20.
    You, W., Mathieu, B., Truong, P., Peltier, J.-F., Simon, G.: DiPIT: a distributed bloom-filter based pit table for CCN nodes. In: 2012 21st International Conference on Computer Communications and Networks (ICCCN), pp. 1–7 (2012)Google Scholar
  21. 21.
    Li, Z., Bi, J., Wang, S., Jiang, X.: Compression of pending interest table with bloom filter in content centric network. In: CFI 2012: Proceedings of the 7th International Conference on Future Internet Technologies, pp. 1–4 (2012)Google Scholar
  22. 22.
    Li, Z., Liu, K., Zhao, Y., Ma, Y.: MaPIT: an enhanced pending interest table for NDN with mapping bloom filter. IEEE Commun. Lett. 18(11), 1915–1918 (2014)CrossRefGoogle Scholar
  23. 23.
    Matteo, V., Diego, P., Linguaglossa, L.: On the design and implementation of a wire-speed pending interest table. In: 2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), vol. 13, pp. 369–374 (2013)Google Scholar
  24. 24.
    Alubady, R., Hassan, S., Habbal, A.: Pending interest table control management in Named Data Network. J. Netw. Comput. Appl. 111, 99–116 (2018)CrossRefGoogle Scholar
  25. 25.
    Hassan, S., Alubady, R., Habbal, A.: Performance evaluation of the replacement policies for pending interest table. J. Telecommun. Electron. Comput. Eng. 8(10), 125–131 (2016)Google Scholar
  26. 26.
    Alubady, R., Hassan, S., Habbal, A.: HLLR : highest lifetime least request policy for high performance pending interest table. In: 2016 IEEE Conference on Open Systems (ICOS), Langkawi, Malaysia, 10–12 October 2016, HLLR, pp. 42–47 (2016)Google Scholar
  27. 27.
    Buragohain, M., Gudipudi, P., Anwer, Z., Nandi, S.: EQPR : enhancing QoS in named data networking using priority and RTT driven PIT replacement policy. In: ICC 2019 – 2019 IEEE International Conference on Communications (ICC), pp. 1–7 (2019)Google Scholar
  28. 28.
    Mastorakis, S., Afanasyev, A., Moiseenko, I., Zhang, L.: ndnSIM 2.0 : a new version of the NDN simulator for NS-3. University of California, Los Angeles. Technical report NDN-0028, California, Los Angeles, pp. 1–8 (2015)Google Scholar
  29. 29.
    Yao, C., Fan, L., Yan, Z., Xiang, Y.: Long-term interest for realtime applications in the named data network. In: Proceedings of ACM AsiaFI12, pp. 1–8 (2012)Google Scholar
  30. 30.
    Bouk, S.H., Ahmed, S.H., Yaqub, M.A., Kim, D., Gerla, M.: DPEL: dynamic PIT entry lifetime in vehicular named data networks. IEEE Commun. Lett. 20(2), 336–339 (2016)CrossRefGoogle Scholar
  31. 31.
    Alubady, R., Hassan, S., Habbal, A.: Adaptive interest lifetime in named data networking to support disaster area. J. Telecommun. Electron. Comput. Eng. 10(2–4), 29–34 (2018)Google Scholar
  32. 32.
    Alubady, R., Hassan, S., Habbal, A.: Adaptive interest packet lifetime due to pending interest table overflow. Adv. Sci. Lett., 1–5 (2016)Google Scholar
  33. 33.
    Bouk, S.H., Ahmed, S.H., Kim, D., Park, K.J., Eun, Y., Lloret, J.: LAPEL: hop limit based adaptive PIT entry lifetime for vehicular named data networks. IEEE Trans. Veh. Technol. 67(7), 5546–5557 (2018)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Raaid Alubady
    • 1
  • Suhaidi Hassan
    • 2
  • Adib Habbal
    • 3
  1. 1.Information Networks Department, College of Information TechnologyUniversity of BabylonBabylonIraq
  2. 2.InterNetWorks Research Laboratory, School of ComputingUniversiti Utara Malaysia (UUM)SintokMalaysia
  3. 3.Computer Engineering Department, Faculty of EngineeringKarabuk UniversityKarabükTurkey

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